[GRASS-dev] Seasonal temporal granularity

[Veronica Andreo]

Ciao Luca,

Just following the example in t.rast.aggregate.ds manual page, I added a
section for seasonal aggregation [0] to the "Temporal data processing"
wiki, showing how to get astro_seasonal aggregation from a daily time
series. I guess you already solved the problem, but at least it is there
for future reference :)

It would be awesome, anyway, to have astro_season as a predefined
granularity!! Way more simple!!!

Cheers,
Vero

[0]
https://grasswiki.osgeo.org/wiki/Temporal_data_processing/seasonal_aggregation

2015-08-19 10:46 GMT-03:00 Sören Gebbert <soerengebbert at googlemail.com>:

> Hi Luca,
>
> Am 19.08.2015 12:01 schrieb "Luca Delucchi" <lucadeluge at gmail.com>:
> >
> > On 14 August 2015 at 00:35, Sören Gebbert <soerengebbert at googlemail.com>
> wrote:
> > > Hi,
> >
> > Hi,
> >
> > > to reduce a bit of confusion. You can apply a time interval of
> > > arbitrary size to a map layer. Use the input file option of t.register
> > > and specify the interval size in the input file:
> > >
> >
> > yes in t.register there aren't problems...
> >
> > > name|start_time|end_time
> > > map_1|2001-03-22 00:00:00|2001-06-21 00:00:00
> > > map_2|2001-06-21 00:00:00|2001-09-24 00:00:00
> > > map_3|2001-09-24 00:00:00|2001-12-21 00:00:00
> > > map_4|2001-12-21 00:00:00|2002-03-22 00:00:00
> > > ...
> > >
> > > Be aware that time intervals in the temporal framework are left
> > > closed, right open intervals. Hence, the end time is not part of the
> > > interval, but the start time of a potential successor.
> > > This assures gap free creation of temporal topological correct time
> series.
> > >
> > > The computed granularity of the resulting space-time dataset (STDS)
> > > will be 1 day, since 1 day is the greatest common divider of all the
> > > seasonal time intervals in the STDS.
> > > IMHO, there is no urgent need to support a user defined granularity in
> > > the temporal framework. The Gregorian Calendar hierarchy is almost
> > > sufficient.
> > >
> >
> > for the aggregation I think this is needed...
> > how can I calculate average seasonal temperature starting from a daily
> > temperatures temporal dataset?
>
> Use t.rast.aggregate.ds, the input is the daily strds, the sampling stds
> should have seasonal intervals. Then use average as method. The output will
> have seasonal aggregated temperatures.
>
> Best regards
> Soeren
>
> >
> > > Best regards
> > > Soeren
> > >
> >
> >
> > --
> > ciao
> > Luca
> >
> > http://gis.cri.fmach.it/delucchi/
> > www.lucadelu.org
>
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>
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